Multi-antenna receiver interference cancellation method and apparatus

ABSTRACT

A composite signal including a plurality of component signal streams is processed using QR-decomposition to detect symbols and calculate a decision metric for each of the signal streams ( 202 ). Soft serial interference cancellation is performed on the composite signal based on the symbols detected for different ones of the signal streams and a ranking of the signal streams ( 204 ). The symbols are re-detected and the decision metric re-calculated for each signal stream based on soft serial interference cancellation results ( 206 ). The different decision metric calculations for at least one of the signal streams are compared to determine whether symbol detection is more accurate with or without soft serial interference cancellation ( 208 ). The signal streams are decoded using symbols detected based on soft serial interference cancellation results when symbol detection is determined to be more accurate with soft serial interference cancellation ( 210 ). Otherwise, the streams are decoded based on the symbols detected using QR-decomposition ( 210 ).

TECHNICAL FIELD OF THE INVENTION

The present invention generally relates to multiple-inputmultiple-output (MIMO) based communication networks, and particularlyrelates to cancelling signal interference in MIMO based networks.

BACKGROUND

MIMO (Multiple Input and Multiple Output) is an essential technology toincrease peak data rate or throughput for wireless communications. In aMIMO-based system, the transmitter has multiple antennas fortransmitting information to a receiver. Each transmit antenna radiatesenergy representing the signal being transmitted. The receiver also hasmultiple antennas for receiving the transmitted signals. The signalreceived at each antenna has contributions from different ones of thetransmit antennas. In a case of multi-layer transmission, wheredifferent transmission antenna transmit different information and in acase where there is no feedback information about the channel to thetransmitter, the receiver attempts to separate out the differenttransmit antenna signal components.

A MIMO-based receiver separates out the signal received at the sameantenna into respective individual signal streams transmitted from eachtransmit antenna. As for signal separation processing, MLD (MaximumLikelihood Detection), which could extract antenna diversity gain, givesthe best performance. MLD calculates a metric based on squared Euclideandistance for every possible combination of modulation signals fromreceived signals and selects the modulation signal combination whichshows the maximum likelihood (minimum sum of the metric corresponds tothe combination of modulation signal over streams). The complexityassociated with MLD increases exponentially as a function of modulationorder or number of transmit antenna, and thus becomes even moreimpractical for advanced wireless communication networks.

One conventional approach for separating out multiple antenna signalstreams based on MLD involves combining QR-decomposition with theM-algorithm (QRM-MLD). QRM-MLD reduces the amount of signal processingcompared to MLD while yielding similar performance. QR-decompositioninvolves decomposing a composite channel matrix associated with allsignal propagation paths into a unitary matrix Q and an upper-triangularmatrix R. The Hermitian matrix of Q is then calculated and multipliedwith the matrix representing all received signal streams. This yields anupper-triangular matrix for the desired signal streams, plus noise. Thebottom row of the resulting matrix includes only a particular signalstream without any interference from the other signal streams. Thisreduces the amount of signal processing resources needed to cancelinter-stream interference. Next, the M-algorithm selects a number ofsymbols according to the branch metric by M in metric calculation tocompare at each stage corresponding to transmit antenna which furtherreduces the amount of metric calculations. However, QR-MLD still tendsto be overly complex.

Another conventional approach employed in multi-antenna receivers isSuccessive Interference Cancellation (SIC). According to SIC, receivedsignal streams are ranked, e.g., based on received power. The highestranking stream is selected and a replica of that signal is regeneratedbased on symbols detected for that signal and the estimated channelresponse associated with the signal. The signal replica is thensubtracted from the composite signal, cancelling the signal's influenceon the composite signal. This way, symbols for the remaining signalstreams can be detected absent interference from cancelled signalstreams. The SIC process continues until all signal streams aredetected. Detection performance improves with SIC as more signal streamsare cancelled because the remaining signal streams can be detected withless interference. However, the performance of SIC is typically worsethan MLD because antenna diversity gain is not expected for the firstsignal stream and only 2^(nd) order diversity gain is expected for thesecond signal stream and so on. Generally, when the number of Tx antennais T and the number of Rx antenna is R, ideal diversity order expectedat n-th stream signal detection using SIC is (R−T+n) because it includesthe signal of stream by (T−n+1) among R antennas at n-th signal streamdetection. This may result in improper signal stream detection which inturn causes an erroneous signal replica to be cancelled, increasinginterference for the remaining signal streams.

Yet another conventional interference cancellation approach involvescombining iterative soft cancellation with parallel-type interferencecancellation, e.g., as disclosed in the Watanabe et al. IEICE articleentitled “A Study of MIMO System with QR Decomposition and SoftInterference Canceller”, IEICE Technical Report, RCS2005-112, pp. 31-36,November 2005. This approach uses iterative parallel interferencecancellation using soft values which could get receiver diversity gainand suppress error propagation. QR decomposition gives fairly goodperformance in the initial estimation and cancellation resulting inquick convergence in iterative parallel soft interference cancellation.Then, this approach yields results similar to MLD, but with reducedprocessing. However, complexity is still impractical as well as QRM-MLDand it requires many turbo decoder iterations increasing the time neededto perform signal detection.

SUMMARY

According to the methods and apparatus taught herein, a multi-antennareceiver uses QR-decomposition to detect symbols and calculate adecision metric such as Log Likelihood Ratio (LLR) for each receivedsignal stream over one Transmission Time Interval (TTI) such as oneframe or one sub-frame. The receiver then performs soft serialinterference cancellation and redetects the symbols and recalculates thedecision metric for each received signal stream based on the soft serialinterference cancellation results. The decision metric indicates whethersymbol detection is more accurate with or without soft serialinterference cancellation. Comparing the decision metric calculationsfor at least one of the signal streams allows the receiver to determinewhether soft serial interference cancellation improves symbol detectionaccuracy. If so, the symbols detected based on the interferencecancellation results are decoded and coherently combined to detect thetransmitted signal. Otherwise, the symbols detected before interferencecancellation was performed are decoded. This way, the more accurategroup of detected symbols is used to decode the transmitted signal. Forexample, if soft serial interference cancellation yields too many symboldetection errors as indicated by the decision metric, the resultingsymbols are not decoded. Instead, the symbols detected based on theQR-decomposition results are decoded.

Moreover, the multi-antenna receiver can attempt at least once tore-decode unsuccessfully decoded signal streams. That is, if one or moresignal streams are not properly decoded, the corresponding decodingresults pend while the receiver attempts to decode the remaining signalstreams. Accordingly, the receiver does not stop decoding because onesignal stream was improperly decoded. Instead, the receiver attempts atleast once to re-decode any unsuccessfully decoded signal streams.Decoding accuracy is further improved because interference fromsuccessfully decoded signal streams is cancelled from the compositesignal before re-decoding is attempted. This way, when the receiverattempts to re-decode unsuccessfully decoded signal streams, it does soabsent interference from successfully decoded streams. The receiver mayoptionally re-rank the unsuccessfully decoded signal streams based onthe decision metric calculations before attempting to re-decode thesymbols. This further improves re-decoding accuracy because the signalstreams most likely to be re-decoded successfully are processed firstand their contribution removed before the receiver attempts to re-decodethe remaining signal streams. Attempting more than once to re-decodesignal streams reduces the number of Negative Acknowledgement (NACK)requests issued by the receiver, improving data throughput.

According to one embodiment, a composite signal including a plurality ofcomponent signal streams received by a multi-antenna receiver isprocessed by using QR-decomposition to detect symbols and calculate adecision metric for each of the signal streams. Soft serial interferencecancellation is performed on the composite signal based on the symbolsdetected for different ones of the signal streams and a ranking of thesignal streams. The symbols are re-detected and the decision metricre-calculated for each signal stream based on the soft serialinterference cancellation results. The different decision metriccalculations for at least one of the signal streams are compared todetermine whether symbol detection is more accurate with or without softserial interference cancellation. The signal streams are decoded usingthe symbols detected based on the soft serial interference cancellationresults when symbol detection is determined to be more accurate withsoft serial interference cancellation. Otherwise, the signal streams aredecoded based on the symbols detected using QR-decomposition.

Summarizing the potential effect each component provides, multi-stageiterative soft serial cancellation yields receive antenna diversitygain, soft interference cancellation reduces error propagation due tosymbol detection error or decoding error, QR decomposition reducessymbol detection error, and selection between detected symbols with andwithout cancellation based on a metric reduces decoding error. Ofcourse, the present invention is not limited to the above features andadvantages. Those skilled in the art will recognize additional featuresand advantages upon reading the following detailed description, and uponviewing the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an embodiment of a multi-antenna receiver.

FIG. 2 is a logic flow diagram of an embodiment of processing logic forcancelling interference by a multi-antenna receiver.

FIG. 3 is a logic flow diagram of an embodiment of processing logic forQR-decomposing received signal streams.

FIG. 4 is a logic flow diagram of an embodiment of processing logic forperforming soft serial interference cancellation based on symbolsdetected using QR-decomposition results.

FIG. 5 is a logic flow diagram of an embodiment of processing logic fordetermining whether symbol detection is more accurate with or withoutsoft serial interference cancellation.

FIG. 6 is a logic flow diagram of an embodiment of processing logic fordecoding symbol streams.

FIG. 7 is a logic flow diagram of an embodiment of processing logic forre-decoding symbol streams.

DETAILED DESCRIPTION

FIG. 1 illustrates an embodiment of a receiver 100 having R antennas 102for receiving a signal transmitted over different signal propagationpaths. The signals as a function of time (t) x₁(t), x₂(t), . . . ,x_(R)(t) received at the different antennas 102 each have contributionsfrom different ones of the transmit antennas (not shown). The receivedsignals are filtered, down-converted and digitized by front endcircuitry 104 to form corresponding baseband signal streams as afunction of symbol index (n) x₁(n), x₂(n), . . . , x_(R)(n). Thecomposite baseband signal vector x=[x₁(n), x₂(n), . . . x_(R)(n)]^(T) isprocessed by a baseband processor 106 included in the receiver 100 todecode the transmitted signal.

In one embodiment, the baseband processor 106 detects symbols for eachsignal stream before and after performing interference cancellation onthe composite baseband signal. A decision metric is also calculated foreach signal stream before and after interference cancellation. Thedecision metric indicates symbol detection accuracy. The basebandprocessor 106 compares the decision metric calculations for at least oneof the signal streams to determine whether symbol detection is moreaccurate with or without interference cancellation. If more accurate,the baseband processor 106 uses the symbols detected based on theinterference cancellation results to decode the transmitted signal.Otherwise, the symbols detected before interference cancellation areused for decoding. This way, the more accurate group of symbols is usedto decode the transmitted signal.

In another embodiment, the baseband processor 106 attempts at least onceto re-decode unsuccessfully decoded signal streams. This way, signaldecoding does not stop if only a single stream is incorrectly decoded.Instead, the baseband processor 106 makes at least one attempt tore-decode unsuccessfully decoded signal streams before requestingre-transmission. Accordingly, the baseband processor 106 not only usesthe more accurate group of detected symbols to decode the transmittedsignal, the baseband processor 106 also attempts to re-decodeunsuccessfully decoded signal streams at least once before requestingre-transmission because subtracting interference when decoding issuccessful could reduce interference and improve decoding performance atthe next trial. The baseband processor 106 thus not only improves signaldecoding accuracy, it also improves data transmission throughput byreducing the number of signal re-transmission requests (e.g., NACKs)made by the receiver 100.

In more detail, the baseband processor 106 includes a plurality ofstages 108-116 for processing the composite baseband signal x=[x₁(n),x₂(n), . . . x_(R)(n)]^(T) to recover the transmitted signal. For easeof explanation and illustration only, the number of transmitted symbolstreams is the same as the number of receive antennas 102 (R). However,this may not always be the case. Accordingly, the equations andcorresponding Figures described herein can be readily modified toinclude an additional index (not shown) for generalizing to any numberof transmit and receive antennas. Thus, any number of transmit andreceive antennas can be handled by the embodiments described herein.With this understanding, the different stages 108-116 may be implementedas separate logical and/or software stages. Alternatively, the differentbaseband processor stages 108-116 may be implemented as a single logicalentity and/or software program. Either way, the stages 108-116 shown inFIG. 1 merely illustrate the various signal processing functions carriedout by the baseband processor 106 and should not be construed orotherwise limit the claimed invention to a particular physicalarrangement of logic and/or software elements.

The first baseband processor stage 108 applies QR-decomposition to thereceived signal streams x₁(n), x₂(n), . . . , x_(R)(n), e.g., asillustrated by Step 200 of FIG. 2. The first stage 108 detects symbolsŜ₁ (R)=ŝ_(1,1), ŝ_(1,2), . . . , ŝ_(1,R) and calculates a decisionmetric M₁(R)=m_(1,1), m_(1,2), . . . , m_(1,R) for each signal streamx₁(n), x₂(n), . . . , x_(R)(n) based on the QR-decomposition results,e.g., as illustrated by Step 202 of FIG. 2. The second basebandprocessor stage 110 performs soft serial interference cancellation onthe composite baseband signal x using the first group of detectedsymbols Ŝ₁(R), e.g., as illustrated by Step 204 of FIG. 2. Theinterference cancellation is considered “soft” because symbol estimates(i.e., detected symbols) are used, not actually decoded symbols. Thesecond stage 110 also re-detects the symbols ŝ_(2,1), ŝ_(2,2), . . . ,ŝ_(2,R)=Ŝ₂(R) and re-calculates the decision metric m_(2,1), m_(2,2),m_(2,R)=M₂(R) for each signal stream averaged over symbols within onetransmit time interval (typically one frame or one-sub frame) based onthe soft serial interference cancellation results, e.g., as illustratedby Step 206 of FIG. 2.

The third baseband processor stage 112 compares the different decisionmetric calculations for at least one of the signal streams to determinewhether symbol detection is more accurate with or without soft serialinterference cancellation, e.g., as illustrated by Step 208 of FIG. 2.In one embodiment, LLR is used as the decision metric. In anotherembodiment, the decision metric is a SINR (signal tointerference-plus-noise ratio). In yet another embodiment, theModulation and Coding Set (MCS) associated with each signal stream isused as the decision metric. Those skilled in the art will readilyrecognize that other metrics suitable for indicating symbol detectionaccuracy may also be used. Regardless, if the decision metric indicatessymbol detection is more accurate without soft serial interferencecancellation, the third stage 112 selects the first group of symbolsŜ₁(R) detected based on the QR-decomposition results. Otherwise, thethird stage 112 selects the second group of symbols Ŝ₂(R) detected basedon the interference cancellation results.

The fourth baseband processor stage 114 decodes the different signalstreams using the selected group of symbols, e.g., as illustrated byStep 210 of FIG. 2.

Accordingly, the fourth stage 114 performs symbol decoding based on thesoft serial interference cancellation results when the decision metricindicates that interference cancellation yields more accurate symboldetection results. Otherwise, the signal streams are decoded based onthe QR-decomposition results. The fourth stage 114 may decode the signalstreams via any known symbol decoding technique.

The fifth baseband processor stage 116 determines whether individualones of the signal streams are decoded properly. In one embodiment, thefifth stage 116 calculates a cyclic redundancy check (CRC) value foreach signal stream as is well known in the art. The CRC value indicateswhether symbols detected for a particular signal stream are properlydecoded. If so, the received signal stream is regenerated possibly withsome weighting and partly removed from the composite baseband signal sothat its signal contribution is partly cancelled. This way, theremaining signal streams can be decoded reduced or ideally absentinterference from previously decoded signal streams. In one embodiment,a signal stream may be regenerated by re-encoding decoded symbols tocorresponding soft symbol estimates. The soft symbol estimates aresubjected to an estimate of the channel (i.e., signal propagation path)that carried the signal stream as given by:x _(regen) =α·H _(j) ^(est)(k,n)·s _(j) ^(regen)(k,n)  (1)where x_(regen) approximates the original signal as received at one ofthe antennas, α represents a weighting factor based on LLR (or mutualinformation in another embodiment), which depends on how muchre-generation signal is correct, H_(j) ^(est) represents the channelestimate associated with the regenerated signal, and s_(j) ^(regen)represents the regenerated symbol values.

On the other hand, the decoding results for unsuccessfully decodedsignal streams pend until the fourth stage 114 decodes all signalstreams a first time. If one or more signal streams are not properlydecoded, the baseband processor 106 attempts at least once to re-decodethem. This way, the receiver 100 does not prematurely request signalstream re-transmissions. Instead, the baseband processor 106 attempts atleast one more time to decode unsuccessfully decoded signal streams.

For example, assume that the mth signal stream x_(m)(n) was initiallydecoded incorrectly. The signal contribution associated with each signalstream successfully decoded after x_(m)(n) is removed from the compositebaseband signal. This way, when the baseband processor 106 attempts tore-decode x_(m)(n), it does so absent interference from each signalstream successfully decoded after signal stream x_(m)(n). During theinitial decoding iteration, signal interference from streams x_(m+1)(n),x_(m+2)(n), . . . , x_(R)(n) was present when x_(m)(n) was firstdecoded. However, if any of the signal streams x_(m+1)(n), x_(m+2)(n), .. . , x_(R)(n) were initially decoded correctly, the correspondinginterference is removed before the baseband processor 106 attempts tore-decode x_(m)(n). This improves overall receiver performance andreduces the number of signal re-transmission requests made by thereceiver 100. Finally, a typical system sends ACK (acknowledgement) forstreams which are successfully decoded. Otherwise, it sends NACK (notacknowledgement) requesting re-transmission for streams which are notsuccessfully decoded.

FIG. 3 illustrates an embodiment of processing logic for QR-decomposingthe baseband signal streams x₁(n), x₂(n), . . . , x_(R)(n). The firstbaseband processor stage 108 begins the QR-decomposition and symboldetection process (Step 300). The signal stream index i is set to i=1 sothat the highest ranking signal stream is selected first for processing(Step 302). The signal streams may be initially ranked based on receivedpower. Regardless, the first stage 108 applies QR-decomposition to thehighest ranking signal stream x₁(n) (Step 304). To illustrate theQR-decomposition process, the composite baseband signal vector x=[x₁(n),x₂(n), . . . x_(R)(n)]^(T) can be expressed in matrix form as given by:x=Hc+n  (2)where H is a channel response matrix, c is a matrix (column vector) oftransmitted signal streams and n is an additive noise term at eachreceive antenna. For the case of four transmit and four receiveantennas, x can be denoted as:

$\begin{matrix}{\begin{bmatrix}x_{1} \\x_{2} \\x_{3} \\x_{4}\end{bmatrix} = {{\begin{bmatrix}h_{11} & h_{21} & h_{31} & h_{41} \\h_{12} & h_{22} & h_{32} & h_{42} \\h_{13} & h_{23} & h_{33} & h_{43} \\h_{14} & h_{24} & h_{34} & h_{44}\end{bmatrix}\begin{bmatrix}c_{1} \\c_{2} \\c_{3} \\c_{4}\end{bmatrix}} + \begin{bmatrix}n_{1} \\n_{2} \\n_{3} \\n_{4}\end{bmatrix}}} & (2)^{\prime}\end{matrix}$

As described previously, any number of transmit and receive antennas canbe considered. In general, x has a size of R×1, H has a size of R×T andc has a size of Tx1, where R is the number of receive antennas 102, T isthe number of transmit antennas and possibly IRT.

Furthermore, h_(j,i) the matrix element of H, denotes the channelresponse between the jth transmit antenna and the ith receive antenna102. Again take for example the case of four transmit and receiveantennas 102. In order to perform QR decomposition to get c₁ at x₄ withno interference from c₂, c₃ and c₄, equation (2)′ is modified as:

$\begin{matrix}{{\begin{bmatrix}x_{1} \\x_{2} \\x_{3} \\x_{4}\end{bmatrix} = {{\begin{bmatrix}h_{41} & h_{31} & h_{21} & h_{11} \\h_{42} & h_{32} & h_{22} & h_{12} \\h_{43} & h_{33} & h_{23} & h_{13} \\h_{44} & h_{34} & h_{24} & h_{14}\end{bmatrix}\begin{bmatrix}c_{4} \\c_{3} \\c_{2} \\c_{1}\end{bmatrix}} + \begin{bmatrix}n_{1} \\n_{2} \\n_{3} \\n_{4}\end{bmatrix}}}{or}} & (3) \\{x = {{H_{1}c_{1}} + n}} & (3)^{\prime}\end{matrix}$where H₁=[h₄,h₃,h₂,h₁] and h_(i)=[h_(j,1),h_(j,2),h_(j,3),h_(j,4)]^(T).c₁ is generated by interchanging row component according to H₁.QR-decomposing H₁ yields the unitary matrix Q₁ and upper-triangularmatrix R₁. The multiplication of the Hermitian matrix Q₁ ^(H) and thecomposite baseband signal x is given by:

$\begin{matrix}\begin{matrix}{y = {Q_{1}^{H}x}} \\{= {{R_{1}c_{1}} + \eta_{1}}}\end{matrix} & (4)\end{matrix}$where:η₁=Q₁ ^(n)  (5)Equations (4) and (5) can be arranged as:

$\begin{matrix}{\begin{bmatrix}y_{1} \\y_{2} \\y_{3} \\y_{4}\end{bmatrix} = {{\begin{bmatrix}r_{41} & r_{31} & r_{21} & r_{11} \\0 & r_{32} & r_{22} & r_{12} \\0 & 0 & r_{23} & r_{13} \\0 & 0 & 0 & r_{14}\end{bmatrix}\begin{bmatrix}c_{4} \\c_{3} \\c_{2} \\c_{1}\end{bmatrix}} + \begin{bmatrix}\eta_{11} \\\eta_{12} \\\eta_{13} \\\eta_{14}\end{bmatrix}}} & (6)\end{matrix}$where the fourth row from equation (6) is given by:y ₄ =r ₁₄ c ₁+η₁₄  (7)

As can be seen from equation (7), the fourth row has no interferencefrom transmitted signal streams c_(j) where j≠1. Similarly, H₂=[h₃,h₄,h₁ h₂] and c₂=[c₃ c₄ c₁ c₂]^(T), H₃=[h₄, h₁ h₂, h₃] and c₃=[c₄ c₁ c₂c₃]^(T) and H₄=[h₁,h₂,h₃,h₄]=H and c₄=[c₁ c₂ c₃ c₄]^(r)=c. In turn,interference-free terms for c₂, c₃ and c₄ can likewise be determinedbased on equations (4)-(6). In the same manner, it is possible to make aQR-decomposition to get c_(w) at x_(z). Any desirable metric may be usedto determine which receive antenna stream x_(z) is QR-decomposed to getc_(w). In one embodiment, this determination is based on received pilotpower for each stream which would be allocated to have no interferenceon each other. In another embodiment, c_(w) is obtained by decomposingat for all z (1, 2, . . . , R) and will be selected which has themaximum estimated SINR.

The first baseband processor stage 108 detects symbols ŝ_(1,1) andcalculates the decision metric m_(1,1) for the first signal stream x₁(n)based on the QR-decomposition results y₄ (Step 306). The first stage 108then determines whether all signal streams have been QR-decomposed asdescribed above (Step 308). If not, the stream index is incremented(Step 310) and the QR-decomposition process repeated for each remainingsignal stream (Steps 304-306). The signal streams may be optionallyre-ranked based on the decision metric calculations after all signalstreams have been QR-decomposed (Step 312). In one embodiment, LLR isused as the decision metric. In another embodiment, the decision metricis a SINR (signal to interference-plus-noise ratio). In yet anotherembodiment, the Modulation and Coding Set (MCS) associated with eachsignal stream is used as the decision metric. This way, soft serialinterference cancellation can be performed using a signal stream rankingthat is based on the decision metric calculations and not receivedpower. Either way, the first stage 108 ends the QR-decomposition andsymbol detection processes after all streams have been processed (Step314). The resulting group of detected symbols Ŝ₁(R) is provided to thesecond stage 110 for performing soft serial interference cancellationand symbol re-detection.

FIG. 4 illustrates an embodiment of processing logic for performing softserial interference cancellation on the composite baseband signal xbased on the group of symbols detected using the QR-decompositionresults. Mainly, each transmitted signal stream is regenerated using thecorresponding symbols detected during QR-decomposition and successivelysubtracted from the composite baseband signal based on signal ranking,e.g., according to equation (1). This way, symbols for the remainingsignal streams can be re-detected with reduced or ideally absentinterference from higher-ranking signal streams. In more detail, thesecond baseband processor stage 110 begins the soft serial interferencecancellation process (Step 400). An iteration index k is set to k=1(Step402) and a signal stream index j is set to j=1(Step 404). Interferencecancellation is performed for k_(max) iterations, where symbols aredetected for all signal streams each iteration. During the firstiteration (Step 406), the second stage 110 initializes the interferencecancellation parameters because symbols have already been detected anddecision metric calculations made by the first stage 108.

A signal regenerator 118 included in or associated with the basebandprocessor 106 regenerates the first signal stream using the initializedparameters. The second stage 110 cancels the regenerated signal from thecomposite baseband signal (Step 410). Here, the regenerated signal, alsoknown as replica, which is obtained from the detected signal andestimated channel with a weighting factor based on metric similar toequation (1). Symbols ŝ_(2,2) are then detected and the decision metriccalculated m_(2,2) for the next highest ranking signal stream withreduced or ideally absent interference from the highest ranking signalstream (Step 412). This process continues until symbols for all signalstreams have been re-detected and cancelled from the composite basebandsignal (Step 414), incrementing the signal stream index j each time(Step 416). Eventually, all signal streams are detected and successivelycancelled from the composite signal. When this occurs, the iterationindex k is incremented by one (Step 418) and the interferencecancellation process is repeated once again for all streams (Steps406-416). The symbol estimates ŝ_(2,1)ŝ_(2,2), . . . ŝ_(2,R) anddecision metric calculations m₂(R) are potentially refined each time theiteration index is incremented. Eventually, the desired number ofinterference cancellation iterations is achieved (Step 420). From thesecond iteration on (from k=2 in FIG. 4), for re-detection of ŝ_(2,j),the replica of the jth detected symbol stream at the last (k−1)iteration ŝ_(2,j) is re-added so that the jth stream can be re-detectedduring subsequent iterations k(2, 3, 4 . . . ).

At this point, symbols ŝ_(2,j) are re-detected and the decision metricm_(2,1) re-calculated for the highest ranking stream (Step 422). Thiscompensates for the initialization process performed when k=1(Steps 406and 408). The second baseband processor stage 110 may optionally re-rankthe streams based on the new decision metric calculations (Step 424).The soft serial interference cancellation process is then terminated(Step 426). The resulting group of detected symbols Ŝ₂(R) and thedecision metric calculations M₂(R) are provided to the third stage 112for determining whether soft serial interference cancellation improvessymbol detection accuracy.

FIG. 5 illustrates an embodiment of processing logic for determiningwhether symbol detection is more accurate with or without soft serialinterference cancellation. Mainly, the third baseband processor stage112 compares the different decision metric calculations provided by thefirst and second stages 108, 110 for at least one of the signal streamsto determine whether soft serial interference cancellation improvessymbol detection accuracy. The third stage 112 begins the symboldetection accuracy determination process (Step 500). In one embodiment,the third stage 112 compares the different decision metric calculationsfor the m highest ranking signal streams. In another embodiment, thethird stage 112 compares the decision metric calculation for the highestranking signal stream post interference cancellation (m_(2,1)) to thedecision metric calculation for the highest ranking signal stream preinterference cancellation (m_(1,1)) (Step 502).

Either way, the symbols Ŝ₁ (R) detected by the first stage 108 beforesoft serial interference cancellation are selected for decoding if thedecision metric indicates they are more accurate (Step 504). Otherwise,the second group of symbols Ŝ₂(R) detected by the second stage 110 isselected for decoding (Step 506). The symbol detection accuracydetermination process then ends (Step 508). The selected group ofsymbols is provided to the fourth baseband processor stage 114 fordecoding.

FIG. 6 illustrates an embodiment of processing logic for decoding theselected group of symbol streams. Mainly, the fourth baseband processorstage 114 decodes the symbols provided by the third stage 112,attempting to re-decode unsuccessfully decoded symbol streams at leastonce. This way, symbol detection accuracy improves while reducing thenumber of signal retransmission requests issued by the receiver 100. Inmore detail, the fourth stage 114 begins the symbol decoding process(Step 600). A signal stream index j is set to j=1 so that the highestranking signal stream is processed first (Step 602). The symbolsassociated with the first stream are decoded and the decision metricrecalculated (Step 604). The fifth baseband processor stage 116calculates a CRC value based on the symbol decoding results {circumflexover (d)}₁ for the first signal stream.

A controller 120 included in or associated with the baseband processor106 determines whether the CRC value is valid (Step 606). If valid, thebaseband processor 106 generates a message such as an Acknowledgement(ACK) message indicating the first signal stream was successfullydecoded (Step 608). When the ACK message is actually sent depends on theHybrid Automatic Repeat-Request (HARQ) protocol. All streams may beacknowledged in the same ACK message or in different messages.Regardless, the signal regenerator 118 reproduces the first signalstream using the successfully decoded symbols {circumflex over (d)}₁ andthe fourth stage 114 cancels the regenerated signal from the compositebaseband signal (Step 610). This way, the remaining symbol streams canbe decoded with reduced or ideally absent interference from the firststream. Optionally, the controller 120 instructs a fine channelestimator 122 included in or associated with the baseband processor 106to calculate a fine channel estimate ĥ₁ ^(fine) associated with thefirst signal stream as is well known in the art (Step 612) (e.g., wellknown as the decision feedback approach). The fine channel estimate ishighly accurate and is used to re-generate the first stream, e.g., bysubstituting the fine channel estimate ĥ₁ ^(fine) for H_(j) ^(st) inequation (1). Using a more accurate channel estimate improvescancellation of the re-generated signal from the composite signal.

Regardless, the symbol decoding process (Steps 604-610) continues foreach signal stream (Steps 614 and 616). If the CRC value calculated fora particular signal stream is invalid, the signal stream is notregenerated and cancelled from the composite signal (Step 606). Instead,its decoding results pend and its decision metric calculation saved forsubsequent use (step 618). The decoding results are not used because thesignal stream was incorrectly decoded. Otherwise, decoding errors arecompounded if they are regenerated and cancelled from the compositesignal. The fourth stage 114 ends the symbol decoding process after eachsymbol stream is initially decoded (Step 620). However, the receiver 100does not automatically generate a signal retransmission request for eachunsuccessfully decoded signal stream. Instead, the baseband processor106 attempts at least once to re-decode the unsuccessfully decodedsignal streams before issuing retransmission requests such as NACKs.

FIG. 7 illustrates an embodiment of processing logic for re-decodingsymbol streams that were initially decoded incorrectly. This way, thereceiver 100 has at least one more opportunity to re-decode problematicsignal streams before requesting retransmission. The fourth basebandprocessor stage 114 re-initiates the symbol re-decoding process (Step700). The unsuccessfully decoded signal streams are re-ranked based onthe decision metric calculations so that the highest ranking signalstream is processed first (Step 702). This improves the likelihood thatsome or all of the problematic signal streams will be correctly decoded.

A signal stream index j is set to j=1(Step 704). Symbols are decoded andthe decision metric recalculated for the jth signal stream (Step 706).The fifth stage 116 calculates a CRC value for the jth signal stream andthe controller 120 determines whether the CRC value is valid (Step 708).This time, the receiver 100 issues a retransmission request if thesymbols remain incorrectly decoded (Step 710). Otherwise, the receiver100 issues an acknowledgement message indicating successful decoding(Step 712) if the CRC value is valid. The re-decoding process continuesfor the remaining signal streams until the last stream (as indicated byN_(UD)) is re-decoded (Steps 714 and 716). The fourth stage 114 thenends the symbol re-decoding process (Step 718). The symbol re-decodingprocess may be repeated as many times as desired, each iterationeliciting steps 700-718 of FIG. 7 so long as decision metric increaseseach iteration, even if the CRC value is invalid within the maximumnumber of trials which depends on processing delay, etc.

With the above range of variations and applications in mind, it shouldbe understood that the present invention is not limited by the foregoingdescription, nor is it limited by the accompanying drawings. Instead,the present invention is limited only by the following claims, and theirlegal equivalents.

1. A method of processing a composite signal including a plurality ofcomponent signal streams received by a multi-antenna receiver,comprising: using QR-decomposition to detect symbols and calculate adecision metric for each of the signal streams; performing soft serialinterference cancellation on the composite signal based on the symbolsdetected for different ones of the signal streams and a ranking of thesignal streams by regenerating each signal stream from the correspondingsymbols detected using QR-decomposition and cancelling each regeneratedsignal stream from the composite signal in order based on rank;re-detecting the symbols and re-calculating the decision metric for eachsignal stream based on the soft interference cancellation results;comparing the different decision metric calculations for at least one ofthe signal streams to determine whether symbol detection is moreaccurate with or without soft serial interference cancellation; anddecoding the signal streams using the symbols detected based on the softserial interference cancellation results when symbol detection isdetermined to be more accurate with soft serial interferencecancellation, otherwise based on the symbols detected usingQR-decomposition.
 2. The method of claim 1, wherein usingQR-decomposition to detect symbols and calculate a decision metric foreach of the signal streams comprises QR-decomposing the signal streamsto obtain a unitary matrix and a triangular matrix used to detect thesymbols and calculate the decision metric for each signal stream.
 3. Themethod of claim 2, wherein QR-decomposing the signal streams to obtain aunitary matrix and a triangular matrix comprises QR-decomposing thesignal streams based on received pilot power for each stream.
 4. Themethod of claim 2, wherein QR-decomposing the signal streams to obtain aunitary matrix and a triangular matrix comprises QR-decomposing thesignal streams and then selecting the signal stream having the maximumestimated signal to interference-plus-noise ratio.
 5. The method ofclaim 1, wherein the symbols are detected and the decision metriccalculated for all signal streams using QR-decomposition beforeperforming soft serial interference cancellation on the compositesignal.
 6. The method of claim 1, wherein a higher ranking signal streamis regenerated and cancelled from the composite signal before detectingthe symbols of a lower ranking signal stream so that the symbols of thelower ranking signal stream can be detected from the composite signalabsent interference from the higher ranking signal stream.
 7. The methodof claim 1, further comprising re-ranking the signal streams based onthe decision metric calculated for the different signal streams usingQR-decomposition, wherein the soft serial interference cancellation isperformed based on the re-ranking.
 8. The method of claim 1, whereincomparing the different decision metric calculations for at least one ofthe signal streams to determine whether symbol detection is moreaccurate with or without soft serial interference cancellation comprisescomparing the different decision metric calculations for one or more ofthe highest ranking signal streams.
 9. The method of claim 1, whereindecoding the signal streams comprises: decoding the signal streams inorder based on rank; successively cancelling successfully decoded signalstreams from the composite signal so that remaining non-decoded signalstreams can be subsequently decoded from the composite signal absentinterference from the successfully decoded signal streams; andattempting at least once to re-decode unsuccessfully decoded signalstreams.
 10. The method of claim 9, further comprising: performing finechannel estimation for successfully decoded signal streams; and usingthe corresponding fine channel estimation results to cancel successfullydecoded signal streams from the composite signal.
 11. The method ofclaim 9, further comprising reporting whether the signal streams havebeen successfully or unsuccessfully decoded after attempting at leastonce to re-decode unsuccessfully decoded signal streams.
 12. The methodof claim 9, wherein decoding success is determined based on a cyclicredundancy check (CRC) value determined for each decoded signal stream.13. The method of claim 12, wherein attempting at least once tore-decode unsuccessfully decoded signal streams comprises attempting tore-decode the unsuccessfully decoded signal streams so long as thedecision metric increases each attempt even if one or more of the CRCvalues is invalid.
 14. The method of claim 9, wherein successivelycancelling successfully decoded signal streams from the composite signalcomprises: cancelling a decoded higher ranking signal stream from thecomposite signal if successfully decoded so that a lower ranking signalstream can be decoded from the composite signal absent interference fromthe higher ranking signal stream; and if the higher ranking signalstream is not successfully decoded, decoding the lower ranking signalstream and cancelling the decoded lower ranking signal stream from thecomposite signal if successfully decoded so that the higher rankingsignal stream can be subsequently re-decoded from the composite signalabsent interference from the lower ranking signal stream.
 15. Amulti-antenna receiver for processing a composite signal including aplurality of component signal streams, comprising a baseband processorconfigured to: use QR-decomposition to detect symbols and calculate adecision metric for each of the signal streams; perform soft serialinterference cancellation on the composite signal based on the symbolsdetected for different ones of the signal streams and a ranking of thesignal streams by regenerating each signal stream from the correspondingsymbols detected using QR-decomposition and cancelling each regeneratedsignal stream from the composite signal in order based on rank;re-detect the symbols and re-calculate the decision metric for eachsignal stream based on the soft serial interference cancellationresults; compare the different decision metric calculations for at leastone of the signal streams to determine whether symbol detection is moreaccurate with or without soft serial interference cancellation; anddecode the signal streams using the symbols detected based on the softserial interference cancellation results when symbol detection isdetermined to be more accurate with soft serial interferencecancellation, otherwise based on the symbols detected usingQR-decomposition.
 16. The multi-antenna receiver of claim 15, whereinthe baseband processor is configured to QR-decompose the signal streamsto obtain a unitary matrix and a triangular matrix used to detect thesymbols and calculate the decision metric for each signal stream. 17.The multi-antenna receiver of claim 15, wherein the baseband processoris configured to detect the symbols and calculate the decision metricfor all signal streams using QR-decomposition before performing softserial interference cancellation on the composite signal.
 18. Themulti-antenna receiver of claim 15, wherein the baseband processor isconfigured to regenerate and cancel a higher ranking signal stream fromthe composite signal before detecting the symbols of a lower rankingsignal stream so that the symbols of the lower ranking signal stream canbe detected from the composite signal absent interference from thehigher ranking signal stream.
 19. The multi-antenna receiver of claim15, wherein the baseband processor is configured to re-rank the signalstreams based on the decision metric calculated for the different signalstreams using QR-decomposition, wherein the soft serial interferencecancellation is performed based on the re-ranking.
 20. The multi-antennareceiver of claim 15, wherein the baseband processor is configured to:decode the signal streams in order based on rank; successively cancelsuccessfully decoded signal streams from the composite signal so thatremaining non-decoded signal streams can be subsequently decoded fromthe composite signal absent interference from the successfully decodedsignal streams; and attempt at least once to re-decode unsuccessfullydecoded signal streams.
 21. The multi-antenna receiver of claim 20,wherein the baseband processor is configured to: perform fine channelestimation for successfully decoded signal streams; and use thecorresponding fine channel estimation results to cancel successfullydecoded signal streams from the composite signal.
 22. The multi-antennareceiver of claim 20, wherein the baseband processor is configured todetermine decoding success based on a cyclic redundancy check (CRC)value calculated for each decoded signal stream.
 23. The multi-antennareceiver of claim 20, wherein the baseband processor is configured to:cancel a decoded higher ranking signal stream from the composite signalif successfully decoded so that a lower ranking signal stream can bedecoded from the composite signal absent interference from the higherranking signal stream; and if the higher ranking signal stream is notsuccessfully decoded, decode the lower ranking signal stream andcancelling the decoded lower ranking signal stream from the compositesignal if successfully decoded so that the higher ranking signal streamcan be subsequently re-decoded from the composite signal absentinterference from the lower ranking signal stream.